Evolution of COVID-19 mortality over time: results from the Swiss hospital surveillance system (CH-SUR)

BACKGROUND When the periods of time during and after the first wave of the ongoing SARS-CoV-2/COVID-19 pandemic in Europe are compared, the associated COVID-19 mortality seems to have decreased substantially. Various factors could explain this trend, including changes in demographic characteristics of infected persons and the improvement of case management. To date, no study has been performed to investigate the evolution of COVID-19 in-hospital mortality in Switzerland, while also accounting for risk factors. METHODS We investigated the trends in COVID-19-related mortality (in-hospital and in-intermediate/intensive-care) over time in Switzerland, from February 2020 to June 2021, comparing in particular the first and the second wave. We used data from the COVID-19 Hospital-based Surveillance (CH-SUR) database. We performed survival analyses adjusting for well-known risk factors of COVID-19 mortality (age, sex and comorbidities) and accounting for competing risk. RESULTS Our analysis included 16,984 patients recorded in CH-SUR, with 2201 reported deaths due to COVID-19 (13.0%). We found that overall in-hospital mortality was lower during the second wave of COVID-19 than in the first wave (hazard ratio [HR] 0.70, 95% confidence interval [CI] 0.63- 0.78; p <0.001), a decrease apparently not explained by changes in demographic characteristics of patients. In contrast, mortality in intermediate and intensive care significantly increased in the second wave compared with the first wave (HR 1.25, 95% CI 1.05-1.49; p = 0.029), with significant changes in the course of hospitalisation between the first and the second wave. CONCLUSION We found that, in Switzerland, COVID-19 mortality decreased among hospitalised persons, whereas it increased among patients admitted to intermediate or intensive care, when comparing the second wave to the first wave. We put our findings in perspective with changes over time in case management, treatment strategy, hospital burden and non-pharmaceutical interventions. Further analyses of the potential effect of virus variants and of vaccination on mortality would be crucial to have a complete overview of COVID-19 mortality trends throughout the different phases of the pandemic

The fast transient sky with Gaia

The ESA Gaia satellite scans the whole sky with a temporal sampling ranging from seconds and hours to months. Each time a source passes within the Gaia field of view, it moves over 10 CCDs in 45 s and a lightcurve with 4.5 s sampling (the crossing time per CCD) is registered. Given that the 4.5 s sampling represents a virtually unexplored parameter space in optical time domain astronomy, this data set potentially provides a unique opportunity to open up the fast transient sky. We present a method to start mining the wealth of information in the per CCD Gaia data. We perform extensive data filtering to eliminate known on-board and data processing artefacts, and present a statistical method to identify sources that show transient brightness variations on ~2 hours timescales. We illustrate that by using the Gaia photometric CCD measurements, we can detect transient brightness variations down to an amplitude of 0.3 mag on timescales ranging from 15 seconds to several hours. We search an area of ~23.5 square degrees on the sky, and find four strong candidate fast transients. Two candidates are tentatively classified as flares on M-dwarf stars, while one is probably a flare on a giant star and one potentially a flare on a solar type star. These classifications are based on archival data and the timescales involved. We argue that the method presented here can be added to the existing Gaia Science Alerts infrastructure for the near real-time public dissemination of fast transient events.Comment: 10 pages, 5 figures and 5 tables; MNRAS in pres

All-Cause Mortality and Causes of Death in the Swiss Hepatitis C Cohort Study (SCCS).

With direct-acting antiviral agents (DAAs), mortality rates and causes of death among persons with hepatitis C virus (HCV) infection may change over time. However, the emergence of such trends may be delayed by the slow progression of chronic hepatitis C. To date, detailed analyses of cause-specific mortality among HCV-infected persons over time remain limited. We evaluated changes in causes of death among Swiss Hepatitis C Cohort Study (SCCS) participants from 2008 to 2016. We analyzed risk factors for all-cause and cause-specific mortality, accounting for changes in treatment, fibrosis stage, and use of injectable drugs over time. Mortality ascertainment was completed by linking lost-to-follow-up participants to the Swiss Federal Statistical Office death registry. We included 4700 SCCS participants, of whom 478 died between 2008 and 2016. The proportion of unknown causes of death decreased substantially after linkage, from 42% to 10%. Leading causes of death were liver failure (crude death rate 4.4/1000 person-years), liver cancer (3.4/1000 person-years), and nonliver cancer (2.8/1000 person-years), with an increasing proportion of cancer-related deaths over time. Cause-specific analysis showed that persons with sustained virologic response were less at risk for liver-related mortality than those never treated or treated unsuccessfully. Although the expected decrease in mortality is not yet observable, causes of death among HCV-infected persons have evolved over time. With the wider use of DAAs, liver-related mortality is expected to decline in the future. Continued monitoring of cause-specific mortality will remain important to assess the long-term effect of DAAs and design effective interventions

Hospital Outcomes of Community-Acquired SARS-CoV-2 Omicron Variant Infection Compared With Influenza Infection in Switzerland

IMPORTANCE: With the ongoing COVID-19 pandemic, it is crucial to assess the current burden of disease of community-acquired SARS-CoV-2 Omicron variant in hospitalized patients to tailor appropriate public health policies. Comparisons with better-known seasonal influenza infections may facilitate such decisions. OBJECTIVE: To compare the in-hospital outcomes of patients hospitalized with the SARS-CoV-2 Omicron variant with patients with influenza. DESIGN, SETTING, AND PARTICIPANTS: This cohort study was based on a national COVID-19 and influenza registry. Hospitalized patients aged 18 years and older with community-acquired SARS-CoV-2 Omicron variant infection who were admitted between January 15 and March 15, 2022 (when B.1.1.529 Omicron predominance was >95%), and hospitalized patients with influenza A or B infection from January 1, 2018, to March 15, 2022, where included. Patients without a study outcome by August 30, 2022, were censored. The study was conducted at 15 hospitals in Switzerland. EXPOSURES: Community-acquired SARS-CoV-2 Omicron variant vs community-acquired seasonal influenza A or B. MAIN OUTCOMES AND MEASURES: Primary and secondary outcomes were defined as in-hospital mortality and admission to the intensive care unit (ICU) for patients with the SARS-CoV-2 Omicron variant or influenza. Cox regression (cause-specific and Fine-Gray subdistribution hazard models) was used to account for time-dependency and competing events, with inverse probability weighting to adjust for confounders with right-censoring at day 30. RESULTS: Of 5212 patients included from 15 hospitals, 3066 (58.8%) had SARS-CoV-2 Omicron variant infection in 14 centers and 2146 patients (41.2%) had influenza A or B in 14 centers. Of patients with the SARS-CoV-2 Omicron variant, 1485 (48.4%) were female, while 1113 patients with influenza (51.9%) were female (P = .02). Patients with the SARS-CoV-2 Omicron variant were younger (median [IQR] age, 71 [53-82] years) than those with influenza (median [IQR] age, 74 [59-83] years; P < .001). Overall, 214 patients with the SARS-CoV-2 Omicron variant (7.0%) died during hospitalization vs 95 patients with influenza (4.4%; P < .001). The final adjusted subdistribution hazard ratio (sdHR) for in-hospital death for SARS-CoV-2 Omicron variant vs influenza was 1.54 (95% CI, 1.18-2.01; P = .002). Overall, 250 patients with the SARS-CoV-2 Omicron variant (8.6%) vs 169 patients with influenza (8.3%) were admitted to the ICU (P = .79). After adjustment, the SARS-CoV-2 Omicron variant was not significantly associated with increased ICU admission vs influenza (sdHR, 1.08; 95% CI, 0.88-1.32; P = .50). CONCLUSIONS AND RELEVANCE: The data from this prospective, multicenter cohort study suggest a significantly increased risk of in-hospital mortality for patients with the SARS-CoV-2 Omicron variant vs those with influenza, while ICU admission rates were similar

Short timescale variability in the Gaia era

This doctoral research is focused on the detection and characterization of short timescale astronomical variability, i.e. luminosity variations on timescale shorter than 12h, as part of the whole data processing and analysis for the European Gaia space mission. First I worked on the prediction of Gaia capabilities for identifying short timescale variability from Gaia photometry, by means of variogram analysis, and via light-curve simulations of various short timescale variable types. Then I investigated real Gaia photometry, looking for bona fide short timescale variable candidates from the first 22 months of Gaia data. This exploratory work resulted in a list of 3018 suspected periodic, short timescale variable candidates, published as part of the Gaia Data Release 2 (April 2018). Finally, I was also involved in various observational programs, contributing to Gaia transient events confirmation and open cluster photometric surveys. Moreover I explored the properties of the Deeming period search technique

Mortality trends and causes of death among HIV positive patients at Newlands Clinic in Harare, Zimbabwe

We report trends in mortality patterns and causes among HIV positive patients, who initiated antiretroviral therapy (ART), at an urban clinic in Harare, Zimbabwe

Assessing relative COVID-19 mortality: a Swiss population-based study

Objective: Severity of the COVID-19 has been previously reported in terms of absolute mortality in SARS-CoV-2 positive cohorts. An assessment of mortality relative to mortality in the general population is presented. Design: Retrospective population-based study. Setting: Individual information on symptomatic confirmed SARS-CoV-2 patients and subsequent deaths from any cause were compared with the all-cause mortality in the Swiss population of 2018. Starting 23 February 2020, mortality in COVID-19 patients was monitored for 80 days and compared with the population mortality observed in the same time of year starting 23 February 2018. Participants: 5 102 300 inhabitants of Switzerland aged 35–95 without COVID-19 (general population in spring 2018) and 20 769 persons tested positively for COVID-19 during the first wave in spring 2020. Measurements Sex-specific and age-specific mortality rates were estimated using Cox proportional hazards models. Absolute probabilities of death were predicted and risk was assessed in terms of relative mortality by taking the ratio between the sex-specific and age-specific absolute mortality in COVID-19 patients and the corresponding mortality in the 2018 general population. Results: Absolute mortalities increased with age and were higher for males compared with females, both in the general population and in positively tested persons. A confirmed SARS-CoV-2 infection substantially increased the probability of death across all patient groups at least eightfold. The highest relative mortality risks were observed among males and younger patients. Male COVID-19 patients exceeded the population hazard for males (HR 1.21, 95% CI 1.02 to 1.44). An additional year of age increased the population hazard in COVID-19 patients only marginally (HR 1.00, 95% CI 1.00 to 1.01). Conclusions: Healthcare professionals, decision-makers and societies are provided with an additional population-adjusted assessment of COVID-19 mortality risk. In combination with absolute measures of risk, the relative risks presented here help to develop a more comprehensive understanding of the actual impact of COVID-19

Future scenarios for the SARS-CoV-2 epidemic in Switzerland: an age-structured model

The recent lifting of COVID-19 related restrictions in Switzerland causes uncertainty about the future of the epidemic. We developed a compartmental model for SARS-CoV-2 transmission in Switzerland and projected the course of the epidemic until the end of year 2020 under various scenarios. The model was age-structured with three categories: children (0-17), adults (18-64) and seniors (65- years). Lifting all restrictions according to the plans disclosed by the Swiss federal authorities by mid-May resulted in a rapid rebound in the epidemic, with the peak expected in July. Measures equivalent to at least 76% reduction in all contacts were able to eradicate the epidemic; a 54% reduction in contacts could keep the intensive care unit occupancy under the critical level and delay the next wave until October. In scenarios where strong contact reductions were only applied in selected age groups, the epidemic could not be suppressed, resulting in an increased risk of a rebound in July, and another stronger wave in September. Future interventions need to cover all age groups to keep the SARS-CoV-2 epidemic under control

Short time-scale variables in the gaia era: detection and characterization by structure function analysis

We investigate the capabilities of the ESA Gaia mission for detecting and characterizing short time-scale variability, from tens of seconds to a dozen hours. We assess the efficiency of the variogram analysis, for both detecting short time-scale variability and estimating the underlying characteristic time-scales from Gaia photometry, through extensive light-curve simulations for various periodic and transient short time-scale variable types. We show that, with this approach, we can detect fast periodic variability, with amplitudes down to a few millimagnitudes, as well as some M dwarf flares and supernovae explosions, with limited contamination from longer time-scale variables or constant sources. Time-scale estimates from the variogram give valuable information on the rapidity of the underlying variation, which could complement time-scale estimates from other methods, like Fourier-based periodograms, and be reinvested in preparation of ground-based photometric follow-up of short time-scale candidates evidenced by Gaia. The next step will be to find new short time-scale variable candidates from real Gaia data, and to further characterize them using all the Gaia information, including colour and spectrum